| 개인 맞춤형 의료를 위한 생성형 인공지능 활용 임상 한의학 실습 교육 사례 |
박미소1 
, 전주현2
, 허준영1
, 류호룡1
, 이지연3
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1대전대학교 한의과대학 심계내과학교실
2대전대학교 한의과대학 침구의학교실
3대전대학교 한의과대학 부인과학교실 |
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| Integrating Generative AI into Clinical Practice Education: Enhancing Personalized Medicine Delivery Skills for Korean Medicine Students |
| Miso S. Park1
, Ju Hyun Jeon2
, Junyoung Hur1
, Horyong Yoo1
, and Ji-Yeon Lee3
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1Department of Cardiology and Neurology of Korean Medicine, College of Korean Medicine, Daejeon University
2Department of Acupuncture and Moxibustion Medicine, College of Korean Medicine, Daejeon University
3Department of Obstetrics and Gynecology of Korean Medicine, College of Korean Medicine, Daejeon University |
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| Corresponding Author:
Ji-Yeon Lee ,Tel: +82-42-470-9139, Fax: +82-42-470-9009, Email: jyounl@daum.net |
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Received: January 21, 2025; Revised: February 18, 2025. Accepted: February 21, 2025. |
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| ABSTRACT |
Objectives: We aimed to explore the use of generative AI, specifically ChatGPT, in clinical practice education for Korean Medicine (KM) students. We focused on enhancing their ability to provide personalized lifestyle guidance and analog-type symptom-tracking tools for managing chronic non-communicable diseases (NCDs).
Methods: The class was part of a clinical practice course for third-year KM students. The course included role-playing and PBL combined with CBL in four modules: cardiology and neurology I, cardiology and neurology II, gynecology, and acupuncture and moxibustion medicine. In each session, students used ChatGPT 4o to create tailored patient educational materials and symptom diaries based on patient case scenarios. These results were shared and discussed throughout the presentations. After completing all modules, students took a survey to assess their satisfaction with ChatGPT and its potential for future applications.
Results: Students effectively used ChatGPT in all four modules to provide individualized lifestyle advice and symptom records, tailoring the outputs to suit patient needs. When ChatGPT became momentarily unavailable, Claude was utilized as a replacement. Student feedback indicated that generative AI could enhance their understanding of disease-specific lifestyle management and improve their efficiency in creating patient-centered educational materials.
Conclusions: Integrating generative AI into clinical education allows KM students to gain real experience in tailored healthcare delivery. As generative artificial intelligence becomes more extensively employed, various Korean medical college education programs utilizing it should be implemented in the future. |
| Keywords:
Medical education; Korean medicine; Problem-based learning; Generative artificial intelligence; ChatGPT; Personalized medicine |
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